For many people with mobility impairments, essential and simple tasks, as dressing or feeding, require the assistance of dedicated people; thus, the use of robotic devices providing independent mobility can have a large impact on their quality of life. We are working on the development of control architecture for assistive robotic systems operated via high-level Human Machine Interface. In particular, we used a lightweight robot manipulator (7DOF Kinova Jaco2) operated via a Brain Computer Interface (Emotiv Epoc+) to perform autonomous mission. Using the BCI, the user selects an element from a GUI by focusing attention on it and counting how many times it flashes (P300 potential generated via oddball paradigm). The motion of the manipulator is controlled relying on a closed loop inverse kinematic algorithm that simultaneously manages multiple set based and equality-based tasks. The objects and the user’s mouth are recognized and localized using an RGB-D sensor (Kinect one). The software architecture is developed relying on widely used frameworks to operate BCIs and robots (namely, BCI2000 for the operation of the BCI and ROS for the control of the robot) integrating control, perception and communication modules developed for the application at hand.
Underwater Assistive Control
An operator drives the vehicle (a model of the Girona 500 vehicle in an underwater scenario, running on Gazebo simulator), enabling/disabling several tasks from an user-friendly interface (developed in Qt). The control framework, based on the Set-based Task Priority Inverse Kinematics control algorithm, reduces the complexity of the operation allowing the operator to focus only on the operational tasks while the safety-related ones and their priorities are autonomously handled by the system.
Coordinated multi-UAVMS control
In this work we developed a Control software Architecture for Coordinated multiple unmanned Aerial Vehicle-manIpulator Systems (CAVIS). The main objective of the developed architecture is to cover the control strategy needed in the framework of the European Project FP7-IP: Aerial Robotics Cooperative Assembly System (ARCAS), in particular, and to support the wide spectrum of aerial vehicle manipulator systems applications. To attain multiple control objectives simultaneously within this architecture, a library of elementary behaviors is developed; then, multiple elementary behaviors are combined, in a given priority order, into tasks (compound behaviors); to this aim the Null-Space-based Behavioral (NSB) approach has been adopted.
- Support multiple UAVMSs with the corresponding physical constraints such as, e.g., actuator limits;
- Supporting heterogeneous vehicles in both the attached manipulator and sensor equipments;
- Compatibility with cooperative scenarios;
- Providing libraries of functionalities that support objectives of the robotics system;
- Insuring the safety of the system by avoiding unexpected obstacles.
Distributed multi-robot system
With the final aim of developing and testing distributed control algorithms, we at first build up a completely distribute experimental set-up composed of several Khepera III mobile robots equipped with Laser Range Finder (LRF) and communicating via ad-hoc wireless network. Video 1 shows preliminary experiments to test a localization algorithm (a feature-based Extended Kalman Filter) that allows the robots to navigate in indoor environment (structured environment and corridor) using the Null-Space based Behavioral control as a motion control to navigate towards waypoints. Then, video 2 shows a formation tracking control experiment using a distributed controller-observer schema.
3D underwater coverage/patrolling strategies
The work described above has been implemented a a 3D scenario by two autonomous underwater vehicles of the class Folaga.
The video on the side is one of the final experiments for the European project Co3AUV. It has been achieved during February 2012 in collaboration with GraalTech at the NURC (NATO Undersear Research Center) site.
Multi-robot formation control
A multi-robot system made up of Khepera II mobile robots performing a formation control mission and escorting/entraping mission. Video 1: the robots have to reach and keep a linear formation while a dynamic obstacle moves across them. Video 2: the robots have to surround an autonomous target (a tennis ball pushed by hand). The system is robust to the loss of one or more robots.